Documents having image data at high resolutions require very large amounts of storage space. Such documents having image data at high resolutions are typically subjected to some form of data compression in order to avoid the high costs that would be associated with storing the documents.
Such image data, when derived from natural sources such as digital camera or scanners, contain random noise due to the capture process. Synthetically generated image data typically do not contain such noise.
“Lossless” compression methods, such as Lempel-Ziv Welch (LZW), do not perform particularly well on portions of a document that contain noisy pixel maps (continuous-tone pixel maps with inherent random noise or noisy images).
On the other hand, “lossy” methods such as JPEG work fairly well on continuous-tone pixel maps with inherent random noise (noisy images), but the “lossy” methods do not work particularly well on the parts of the document that contain text.
As illustrated in FIG. 1, a conventional image data path for rendering image data includes an image data source 10. As noted above, image data is subjected to data compression to reduce memory requirements for the image data.
The image data from the image data source 10 is lossless compressed by a lossless compression system 20 prior to being stored in a memory 30. When image data is to be rendered by a print engine 50, the compressed image data is read from the memory 30 and then decompressed by a decompression system 40.
The decompressed image data is transmitted to the print engine 50, wherein the print engine 50 converts the decompressed image data to a printed image on a recording medium.
However, as noted above, since the conventional compression/decompression system of FIG. 1 uses a single compression method, lossy or lossless, the conventional compression/decompression system fails to effectively compress noisy image data, such as continuous-tone pixel maps, if the conventional compression method is lossless or fails to preserve image quality on text if the conventional compression method is lossy.
Thus, it is desirable that an adaptive compression/decompression system which can effectively losslessly compress noisy image data, while still producing good results for text.